Range sensing techniques are useful in many computer vision applications. Vision-based range sensing techniques have been investigated in the computer vision literature for many years; for example, they are described in D. Ballard and C. Brown, Computer Vision, Prentice Hall, 1982. These techniques require either structured active illumination projectors as in K. Pennington, P. Will, and G. Shelton, “Grid coding: a novel technique for image analysis. Part 1. Extraction of differences from scenes”, IBM Research Report RC-2475, May, 1969; M. Maruyama and S. Abe, “Range sensing by projecting multiple slits with random cuts”, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 15, No. 6, pp. 647-651, June, 1993; and U.S. Pat. No. 4,269,513 “Arrangement for Sensing the Surface of an Object Independent of the Reflectance Characteristics of the Surface”, P. DiMatteo and J. Ross, May 26, 1981, or multiple input camera devices as in J. Clark, “Active photometric stereo”, Proceedings IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 29-34, June, 1992; and Sishir Shah and J. K. Aggarwal, “Depth estimation using stereo fish-eye lenses, IEEE International Conference on Image Processing, Vol. 1, pp. 740-744, 1994; or cameras with multiple focal depth adjustments as in S. Nayar, M. Watanabe, and M. Noguchi, “Real-time focus range sensor”, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 18, No. 12, pp. 1186-1197, 1996; all of which are expensive to implement.
The present invention's focus is on range sensing methods that are simple and inexpensive to implement in an office environment. The motivation is to enhance the interaction of users with computers by taking advantage of the image and video capture devices that are becoming ubiquitous with office and home personal computers. Such an enhancement could be, for example, windows navigation using human gesture recognition, or automatic screen customization and log-in using operator face recognition, etc. To implement these enhancements, we use computer vision techniques such as image object segmentation, tracking, and recognition. Range information, in particular, can be used in vision-based segmentation to extract objects of interest from a sometimes complex environment.
To sense range, Pennington et al. cited above, uses a camera to detect the reflection patterns from an active source of illumination projecting light strips. For this technique to work, it is required to project a slit of light in a darkened room or to use a laser-based light source under normal room illumination. Clearly, none of these options are practical in the normal home or office environment.
Accordingly, the present invention envisions a novel and inexpensive method for range sensing using a general-purpose image or video camera, and the illumination of a computer's display as an active source of lighting. As opposed to Pennington's method which uses light striping, we do not require that the display's illumination have any special structure to it.